1. Field of the Invention
The present invention relates to specialized computer architectures for accelerating numerical computations associated with three dimensional image or volumetric processing.
2. Description of Related Art
The needs of advanced research in materials development and the advances in display technology have created a market for computer systems which work with 3-D or volume visualization data sets. One prominent 3-D technology is computerized tomography (CT). CT technology can provide Non-destructive evaluation (NDE) data sets that material designers, medical practitioners, and others want. Off-the-shelf arrays of detectors can acquire sets of projections having as many as 2048.sup.2 projection elements for 3-D image reconstructions having 2048.sup.3 volume elements (voxels) with enough spatial and contrast resolution to make the calculations important for every voxel. However, the computer resources do not meet the requirements to reconstruct such a large image in a practical time frame (e.g. within 1 day).
Advances in parallel-computer hardware and the availability of fast algorithms have considerably reduced the reconstruction time for CT inspections. However, as the size, data-acquisition speed and image spatial resolutions of volumetric inspections have increased, the processing and analysis of these data sets have become severe bottlenecks. The 3-D (multi-slice or cone-beam) reconstruction process in CT is much more time consuming than similar 2-D processes because of the large amounts of data required. The desired image sizes, N.sup.3, can be from 512.sup.3 to 1024.sup.3 or greater voxels. This large amount of data puts a severe strain on current computational resources and those readily available off the shelf. For example, a 512.sup.3 image requires about 500 Mbytes of memory for the volume image (not including memory for 2-D projections) and about 200 hours of processing time on a typical workstation.
Also, there are a variety of technologies within the CT field and from other fields, which require similar processing resources. For instance, cone-beam (3-D) computed tomography utilizes an area detector to collect the information for a complete volume. A set of 2-D projections (radiographs) are acquired and the 2-D data sets can be used to reconstruct directly into a volume (3-D) image. Unfortunately, no one cone-beam reconstruction algorithm has superior performance over the range of cone-beam acquisition modes. It was determined that an ideal reconstructor must be capable of operating with several different types of cone-beam and 2-D reconstruction algorithms. This requirement demands that the reconstructor hardware be general purpose in nature with programmable hardware. Along with the capability to operate on several different types of algorithms, another advantage of a general purpose reconstructor is the ability to accommodate changes in the algorithms at later dates.
An ideal solution for a fast programmable, multiple-algorithm, volume reconstructor is to implement the computationally-intensive portions of the reconstruction algorithms in specialized hardware. However, prior attempts to design such specialized hardware have failed. For instance, Cauquineau, et al., "A Processor Architecture for Image and Volume Reconstruction", published on about the 3rd of Apr., 1990, at the IEEE ICASSP '90 conference in Albuquerque, N.M., discussed the problem. The Cauquineau, et al., article, in fact, proposed an architecture for a "possible" reconstruction module (see, section 4.1 of the article on the third page of the copy provided with the application). However, there is not sufficient detail in the article to enable implementation of the reconstruction module.
Therefore, there is a need for a system which overcomes the computational bottleneck associated with volume visualization type computations. Such system would preferably accommodate a variety of algorithms, and be adaptable to future algorithms.